{"id":"W2809160987","doi":"10.1002/net.21827","title":"A two‐phase Pareto local search heuristic for the bi‐objective pollution‐routing problem","year":2018,"lang":"en","type":"article","venue":"Networks","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Pareto principle; Heuristic; Mathematical optimization; Routing (electronic design automation); Pollution; Phase (matter); Pareto optimal; Computer science; Multi-objective optimization; Mathematics; Chemistry; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001043227,0.0001727845,0.0001711618,0.0000540913,0.0004001701,0.00007788992,0.0002155123,0.000109313,0.00003594333],"category_scores_gemma":[0.0001171546,0.0001421755,0.00007126835,0.0004771687,0.0001647655,0.00007260724,0.00005826471,0.0003079901,0.00001722604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001354424,"about_ca_system_score_gemma":0.00003741791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000317917,"about_ca_topic_score_gemma":0.0000322227,"domain_scores_codex":[0.9986828,0.0001223127,0.0002703443,0.0002337916,0.0001602383,0.0005304873],"domain_scores_gemma":[0.9988475,0.0005533897,0.00004150314,0.0002885507,0.0001822029,0.00008684617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003325702,0.00001390425,0.00007914421,0.00001387997,0.00004951382,8.744956e-7,0.0004865125,0.9387892,0.00003194948,0.0009123056,0.00121601,0.05837338],"study_design_scores_gemma":[0.0009331356,0.0001003738,0.0001719285,0.00004449431,0.00003737391,0.000007737585,0.0002348337,0.9969859,0.0002434183,0.0001844521,0.0008874849,0.0001688362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002361922,0.0002842124,0.9940295,0.0001202519,0.0005243075,0.0006237248,0.0000101535,0.0004054279,0.001640538],"genre_scores_gemma":[0.9386949,0.00001766602,0.05961876,0.0001289413,0.001292423,0.00009173841,0.00000946107,0.0000662261,0.0000799191],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9363329,"threshold_uncertainty_score":0.5797747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02222928959682753,"score_gpt":0.3126692552861101,"score_spread":0.2904399656892825,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}